Make vs Power Automate: The 2026 Comparison

Make vs Power Automate in 2026 comes down to two questions. Are you deep in Microsoft 365? And how much does the visual canvas matter to your team? If you’re on M365 E3/E5 and need RPA or deep enterprise governance, Power Automate is the right answer - bundled licensing, deepest M365 integration, included Power Automate Desktop for RPA. If you want the cleanest visual canvas in the category, broader consumer-SaaS coverage, and you don’t need Microsoft-stack depth, Make wins.

This is the fair head-to-head between the two products. Both are mature, both have real users, both win for the right shape of work.

The 60-second summary

Choose Make if your team thinks visually, your stack is SaaS-broad (not Microsoft-centric), your workflows are moderately complex, and operation volume is moderate.

Choose Power Automate if you’re standardized on Microsoft 365, you need RPA for legacy desktop apps, you have enterprise governance requirements, or you want the deepest M365 integration possible.

Now the long version.

What each tool actually is

Make

Make started as Integromat in 2016, rebranded in 2022 after the Celonis acquisition. It’s a managed SaaS automation platform built around a diagram-style visual canvas. Modules connect with lines, iterators and aggregators are explicit shapes, scenarios run on triggers or schedules.

The signature is the visual canvas - by far the cleanest in the category. Visual thinkers love it. The unit of billing is the operation: every time a module does something (a fetch, a write, an API call), that’s one operation. Plans cap monthly operations.

Power Automate

Power Automate is Microsoft’s workflow automation product. Part of the Power Platform alongside Power Apps, Power BI, Power Virtual Agents / Copilot Studio, and Dataverse. Launched as Microsoft Flow in 2016.

Three products under the umbrella:

• Power Automate Cloud - SaaS workflow automation, the Make-equivalent piece
• Power Automate Desktop - RPA for legacy desktop and web apps
• Power Automate Process Mining - Discovers automation candidates from process logs

Basic Power Automate Cloud is included with most M365 enterprise licenses. Premium connectors, AI Builder, and unattended Desktop bots require additional licensing.

Pricing

The structural difference matters.

Make’s pricing model: per operation. Every module-invocation per record is one operation. Plans range from a free tier (1,000 ops/month) through Core, Pro, Teams, and Enterprise tiers. Pricing scales with operation volume, scenario complexity, and team features.

For a team running 200,000 operations/month on Make, that typically lands in the $200-$500/month range. Iterators that loop over arrays burn operations fast - a scenario processing 500 records may use 1,500+ ops per run.

Power Automate’s pricing model: per user or per flow.

• Per user plan - flat monthly fee per user, each user runs unlimited flows (within fair-use limits).
• Per flow plan - flat monthly fee per individual flow, regardless of how many users trigger it.

Plus basic flows that come bundled with M365 E3/E5 at no extra cost.

If your team is already on M365 E3/E5, basic Power Automate Cloud is effectively free for the bundled scope; additional cost only for premium connectors, AI Builder credits, and Power Automate Desktop unattended bots. For non-Microsoft teams, the Power Automate cost includes the M365 licensing it requires, which is a much bigger commitment.

Run your specific numbers on the workflow cost calculator and against the automation ROI calculator.

The visual canvas: Make’s strongest card

The single biggest reason teams pick Make over Power Automate.

Make’s canvas is a diagram-style visual builder. Each module is a labeled circle, connections between modules are visible lines, iterators and aggregators have distinct shapes, parallel routes branch visibly. At a glance, you can see the shape of a scenario - what it consumes, where it branches, where it merges, what it writes.

Power Automate’s canvas is functional but less visual. Flows are vertical lists of triggers and actions with nested conditions and loops. You can model the same logic, but the visual representation is denser and harder to parse for a team member who didn’t build it.

For visual thinkers, this difference is significant. We’ve seen teams that tried both pick Make on canvas alone, despite the per-operation cost trade-off.

For functional thinkers and Microsoft-native users, Power Automate’s UI is fine - it follows M365 conventions, and the cognitive load isn’t materially different from other M365 admin tooling.

Integrations

Make has ~1,800 first-party apps. The catalog covers most of the consumer and SMB SaaS world - every project tool, every marketing platform, every productivity tool. Strong long-tail consumer SaaS coverage.

Power Automate has ~1,000 official connectors, with the M365 integrations being deeper than anyone else’s. SharePoint, Outlook, Teams, OneDrive, Excel, Dataverse - Power Automate can read and write these in ways no third-party tool can match. Plus the Azure ecosystem connectors, Dynamics, Power BI.

Outside the Microsoft stack, both tools have the major business SaaS connectors. Make has broader long-tail consumer SaaS coverage; Power Automate has deeper enterprise SaaS coverage and unmatched M365 depth.

The practical guidance: if your work touches M365 heavily, Power Automate’s depth there outweighs Make’s breadth elsewhere. If your work is broad across consumer and SMB SaaS in a non-Microsoft stack, Make’s catalog and visual canvas win.

Logic and branching

Both tools handle linear flows fine. They diverge on complex logic.

Make’s primitives are routes (parallel paths), filters (conditional gates on a path), iterators (turn an array into a stream of items), and aggregators (collapse a stream back into a single bundle). Visually elegant. Re-merging routes mid-scenario isn’t always clean; sub-scenarios exist but are less flexible than Power Automate’s nested logic.

Power Automate’s primitives are conditions (if/else), switches (case-based branching), apply-to-each loops, do-until loops, parallel branches, scope blocks with try/catch error handling. More capable for complex enterprise logic. Try/catch in particular is a strong feature for production workflows - you can wrap a sequence of actions in a scope and catch failures cleanly.

For moderately complex SaaS workflows with branching and array iteration, Make’s model is more visually intuitive. For enterprise workflows with try/catch error handling, parallel branches, and complex conditional logic, Power Automate’s primitives are more capable.

Error handling

Make has scenario error handlers - you can attach an error route to any module, and you can configure scenarios to disable themselves after N consecutive failures. The execution log shows what failed and where. Replays work cleanly.

Power Automate has try/catch via scope blocks. You can wrap a sequence of actions in a scope, attach a “run after failure” branch, and route to error-handling actions when anything inside the scope fails. Combined with parallel branches and run-after conditions, this gives you full control over failure paths.

Both tools are competent at error handling. Power Automate’s scope-based try/catch is the cleaner pattern for production work; Make’s per-module error routes are simpler for individual error cases.

RPA / desktop automation

Make doesn’t do RPA. It works with cloud apps that have APIs. Legacy desktop apps without APIs aren’t reachable.

Power Automate Desktop is a full RPA product included with Power Automate. UI automation, screen scraping, form filling on legacy apps, browser automation. It runs on a Windows machine (the bot host) and can be triggered by Power Automate Cloud flows.

This is a major capability gap. If you have legacy desktop applications, packaged software without APIs, or any UI-based work where there’s no programmatic interface, Power Automate handles it natively while Make cannot.

For the broader RPA vs AI vs API-workflow context, see AI automation vs RPA.

AI features

Both tools have shipped AI features.

Make’s AI offering includes OpenAI, Anthropic, and Google modules for individual model calls, plus the Make AI Agents capability (canvas-built agents with module-calling tools). Improved meaningfully over the past year. Good for straightforward “add an LLM to my scenario” use cases.

Power Automate’s AI offering is broader:

• AI Builder - pre-built AI models for document understanding, form processing, prediction, classification. Sold via credit packs.
• Copilot Studio - build conversational AI agents inside M365 with access to Microsoft Graph data.
• Azure OpenAI Service integration - first-class GPT-4 class access with enterprise governance.

For AI agents that operate on Microsoft Graph data, Copilot Studio + Power Automate is the strongest combination available. For general-purpose AI workflow building outside Microsoft, both tools work, but neither is the strongest in the category - that’s n8n or Gumloop. See best AI automation tools.

Enterprise governance

Make has team and enterprise features - multi-user, shared workspaces, role-based access, DevOps with environments on higher tiers. Solid for mid-market and small-enterprise governance needs.

Power Automate has serious enterprise governance: DLP (data loss prevention) policies, environments (dev/test/prod), Power Platform admin center, lifecycle management (ALM via Power Platform), audit logs, RBAC, multi-tenant management.

For enterprise-scale, regulated, or governance-heavy use, Power Automate is meaningfully ahead. For mid-market and SMB use, both are adequate.

Custom code

Make has limited inline JavaScript through the “Tools” module - small transforms, no arbitrary npm packages, no Python. For most users this is fine; if you need actual code, it’s a ceiling.

Power Automate has fewer inline code escape hatches. You can call Azure Functions, custom connectors, or Office Scripts for Excel-heavy work - more capable than Make’s inline code in their scope, but more setup. Pure inline code inside a flow is more limited than n8n or Pipedream.

If you need significant custom code, neither tool is your best bet. n8n’s Code node (full JS/Python) handles that better. See top Zapier alternatives.

Learning curve

Make is somewhere between Zapier and Power Automate on difficulty. The visual canvas is welcoming, the module library is large, the diagram style is intuitive for visual thinkers. A non-technical operator can be productive in a day or two for moderately complex scenarios.

Power Automate is more complex on the surface. The UI is denser, the concepts have more layers (connectors, triggers, actions, conditions, scopes, environments, premium licensing), and the entry experience assumes familiarity with Microsoft 365 conventions. A technical M365-adjacent user is productive in a day or two; a non-technical user takes longer.

Where Make still wins

Being fair:

• Visual clarity. The cleanest canvas in the category - scenarios read like diagrams.
• Broader consumer-SaaS catalog. ~1,800 apps including the long tail.
• Friendlier to non-developers outside the Microsoft stack.
• No Microsoft dependency. If you’re not in the M365 ecosystem, Make doesn’t push you toward one.
• Visual iterators and aggregators. The way Make models loop-over-a-list is explicit and easy to teach.
• Faster on-ramp for SaaS-comfortable teams not already on Microsoft.

Where Power Automate wins

The flip side:

• Bundled with M365. If you already pay E3/E5, basic flows are included.
• Deepest M365 integration. SharePoint, Teams, Outlook, OneDrive at first-class depth.
• RPA capability. Power Automate Desktop for legacy systems.
• Enterprise governance. DLP, environments, audit logs, RBAC, ALM.
• Try/catch scopes. Better error handling primitives for production work.
• Real branching primitives. Conditions, switches, parallel branches, do-until loops.
• AI integration with Microsoft Graph. Copilot Studio + AI Builder for M365-aware agents.
• On-premises data gateway for hybrid environments.

When to pick each

A simple framework:

1. Are you on Microsoft 365 E3/E5? Power Automate. The bundling alone usually justifies it, and the M365 integration is unmatched.

2. Do you need RPA for legacy desktop apps? Power Automate. Make doesn’t do this.

3. Are you a visual-thinking team running mid-complexity SaaS workflows in a non-Microsoft stack? Make. The canvas advantage and broader SaaS catalog win.

4. Are you running complex enterprise workflows with governance and audit requirements? Power Automate. Make’s governance story is lighter.

5. Are you running high-operation-volume work that loops over arrays? Look elsewhere - Make’s per-op pricing hurts at scale, and Power Automate’s per-user/per-flow doesn’t cover serious automation volume cleanly either. n8n is often the answer here.

6. Are you doing serious AI agent work? Power Automate inside the Microsoft estate (via Copilot Studio + Graph). n8n for general-purpose.

A few specific scenarios

Marketing operations team in a SaaS company. Stack is HubSpot, Slack, Notion, Linear, Stripe. Make wins - every connector exists, no Microsoft dependency, clean visual canvas, mid-complexity work fits the model.

Finance ops in a mid-sized enterprise on Microsoft. Stack is Excel, SharePoint, Outlook, Dynamics, plus legacy accounting software. Power Automate wins - bundled with M365, Excel/SharePoint integration depth, Power Automate Desktop handles the legacy software, governance fits the enterprise context.

Customer support team in a SaaS startup. Stack is Zendesk, Slack, Linear, Notion. Make wins for visual clarity and ease; Zapier might also be a fit. Power Automate is overkill.

Enterprise IT team automating internal IT processes. Stack is Azure AD, ServiceNow, Teams, Exchange, hardware procurement, SCCM. Power Automate wins - governance, DLP, RPA, M365 depth, on-prem gateway.

Mid-market ops team with both M365 and broader SaaS. Either works, depending on which side dominates. If most work is M365-centric, Power Automate. If most is broader SaaS with M365 on the side, Make plus the standard M365 connectors.

The alternatives both lose to in some shapes

Neither Make nor Power Automate is the right answer in every situation.

• High-volume operations - both get expensive at scale. n8n (per-execution pricing, self-hostable) is usually the answer.
• Heavy AI / agent work - n8n leads for general-purpose AI workflows. Power Automate competes inside the Microsoft estate.
• Code-first developer teams - Pipedream or n8n self-hosted.
• Embedded automation in a SaaS product - Tray.io or Workato.

See top Zapier alternatives and best automation software for the full landscape.

Migration considerations

If you’re switching between Make and Power Automate, expect:

• 2-6 weeks of work depending on workflow count and complexity
• Different data models - scenarios and flows don’t translate 1:1
• Credential / connection re-creation for every integration
• Some workflows won’t translate cleanly - Make scenarios with heavy iterator/aggregator patterns may need restructuring as Power Automate flows; Power Automate flows leveraging M365 depth may not have equivalent Make modules
• Re-testing in the new environment before cutover

We’ve written about migration patterns broadly in how to migrate from Zapier or Make to n8n - the principles apply for any cross-platform migration.

Related reading

• Zapier vs Power Automate
• n8n vs Make: the 2026 comparison
• Top 10 Microsoft Power Automate use cases
• Make vs Zapier: which automation tool wins?
• Top Zapier alternatives
• Best automation software
• AI automation vs RPA
• n8n automation guide
• AI automation guide
• Workflow cost calculator
• Automation ROI calculator

If you’re trying to decide which automation platform actually fits your business - and where automation will pay back first - our Efficiency Scorecard is the fastest answer. 15 minutes, free, you keep the output regardless.